DocumentCode :
75215
Title :
A Primer on Stochastic Differential Geometry for Signal Processing
Author :
Manton, Jonathan H.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Melbourne, VIC, Australia
Volume :
7
Issue :
4
fYear :
2013
fDate :
Aug. 2013
Firstpage :
681
Lastpage :
699
Abstract :
This primer explains how continuous-time stochastic processes (precisely, Brownian motion and other Itô diffusions) can be defined and studied on manifolds. No knowledge is assumed of either differential geometry or continuous-time processes. The arguably dry approach is avoided of first introducing differential geometry and only then introducing stochastic processes; both areas are motivated and developed jointly.
Keywords :
continuous time systems; differential geometry; signal processing; stochastic processes; Brownian motion; Ito diffusion; continuous-time stochastic process; signal processing; stochastic differential geometry; Differential equations; Linear approximation; Manifolds; Random variables; Stochastic processes; Vectors; Brownian motion; Differential geometry; Itô diffusions; Lie groups; continuous-time stochastic processes; estimation theory on manifolds; stochastic differential equations on manifolds;
fLanguage :
English
Journal_Title :
Selected Topics in Signal Processing, IEEE Journal of
Publisher :
ieee
ISSN :
1932-4553
Type :
jour
DOI :
10.1109/JSTSP.2013.2264798
Filename :
6519312
Link To Document :
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